TY  - JOUR
AU  - Sato, Shahriar
TI  - Artificial Neural Networks for Reinforced Concrete Beams: A Systematic Framework
JO  - Open Access Journal of Engineering Applications
PY  - 2021
VL  - 45
IS  - 1
SP  - 424
EP  - 438
AB  - There remains a pressing need for cost-effective methods to assess reinforced concrete beams in water resource management. The governing equations are solved numerically and the results verified through artificial neural networks. The analysis identified 4 dominant factors that together explain most of the observed variation. These conclusions are likely to hold broader relevance beyond the specific cases examined.
KW  - reinforced concrete beams
KW  - artificial neural networks
KW  - structural health monitoring
KW  - rainfall-runoff modelling
KW  - sustainability
SN  - 3105-7004
DO  - 10.55555/oajea.2021.4501.021
UR  - https://journal.bsaps.com/article/9788
ER  -